DETAILED ACTION
This action is in response to the claims filed 02/12/2026 for Application number 17/760,311. Claims 33, 42, 48, and 52 have been amended and claims 34 and 49 have been canceled. Thus, claims 33, 35-48, and 50-52 are currently pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 33, 35-48 and 50-52 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 33,
Step 1 Analysis: Claim 33 is directed to a process, which falls within one of the four statutory categories.
Step 2A Prong 1 Analysis: Claim 33 recites, in part, The limitations of:
classifying first input data to one of a first number of classes can be considered to be an evaluation in the human mind,
adding the one or more new classes to the first number of classes can be considered to be an evaluation in the human mind
These limitations as drafted, are processes that, under broadest reasonable interpretation, covers performance of the limitation in the mind or with the aid of pen and paper which falls within the “Mental Processes” grouping of abstract ideas.
The limitation of:
wherein the adapting of the first machine learning model further causes the apparatus to set a prior probability distribution for the second machine learning model based on (i) a first posterior probability distribution learned for the first number of classes, and (ii) one or more outputs generated by the second machine learning model responsive to receiving the first input data can be considered to be a mathematical calculation.
This limitation as drafted, is a process that, under broadest reasonable interpretation, covers mathematical calculations which falls within the “Mathematical Concepts” grouping of abstract ideas.
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 Analysis: This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements - “An apparatus comprising: at least one processor, and at least one memory storing instructions which, when executed by the at least one processor, causes the apparatus at least to”, “update the second machine learning model by applying the first input data and the second input data as training data” and “train the second machine learning model using the first input data and the second input data.”. Thus, these elements in the claim are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Please see MPEP 2106.05(f).
Additionally, the claim recites the additional elements – “provide a first machine learning model for…”, “adapt the first machine learning model to provide a second machine learning model by…”. These elements that are recited are only generally linked to the judicial exception. Please see MPEP 2106.05(h).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim further recites: receive an input indicative of one or more new classes to add to the first machine learning model; receive second input data for allocating to the one or more, or each new classes. These limitations are mere data gathering steps and thus is an insignificant extra-solution activity. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim as a whole is directed to an abstract idea.
Step 2B Analysis: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of utilizing a processor and memory to perform the steps of the claimed process amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Additionally, the additional elements of providing a first machine learning and adapting the first machine learning model to provide a second machine learning merely generally links the use of the judicial exception to the additional elements.
Furthermore, the limitation of receive an input indicative of one or more new classes to add to the first machine learning model; receive second input data for allocating to the one or more, or each new classes is well-understood, routine, and conventional, as evidenced by MPEP §2106.05(d)(II)(I), “receiving or transmitting data over a network”. These limitations therefore remain insignificant extra-solution activity even upon reconsideration, and does not amount to significantly more. Even when considered in combination, these additional elements amount to mere instructions to apply the exception using generic computer components, generally linking the judicial exception and insignificant extra-solution activity, which cannot provide an inventive concept. The claim is not patent eligible.
Regarding claim 35, the rejection of claim 33 is further incorporated, and further, the claim recites: wherein the setting of the prior probability distribution for the second machine learning model further causes the apparatus to provide a Gaussian probability distribution with: (i) a mean substantially equal to the mean of the first posterior probability distribution, and (ii) a precision matrix;
This claim recites additional mathematical concepts in addition to the judicial exception identified in the rejection of claim 33, thus recites a judicial exception.
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 36, the rejection of claim 35 is further incorporated, and further, the claim recites: wherein the precision matrix comprises parameters based on derivatives of an expectation of the one or more outputs generated by the second machine learning model, wherein the expectation is with respect to the first posterior probability distribution;
This claim recites additional mathematical concepts in addition to the judicial exception identified in the rejection of claim 33, thus recites a judicial exception.
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 37, the rejection of claim 36 is further incorporated, and further, the claim recites: wherein the adapting of the first machine learning model further causes the apparatus to: provide a second posterior distribution, wherein the second posterior distribution comprises a product of mixtures of Gaussian distributions, each Gaussian distribution having the same covariance matrix; and train the second machine learning model based on a loss function comprising a supervised loss, wherein the supervised loss minimises an upper bound of a divergence between the prior distribution and the second posterior distribution. This claim recites additional mathematical concepts in addition to the judicial exception identified in the rejection of claim 33, thus recites a judicial exception.
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 38, the rejection of claim 33 is further incorporated, and further, the claim recites: wherein the adapting of the first machine learning model further causes the apparatus to: determine that received first input data is either labelled or unlabelled data based on a confidence level associated with the resulting output from its application to the first machine learning model. This claim recites additional mental steps in addition to the judicial exception identified in the rejection of claim 33, thus recites a judicial exception.
The claim further recites: store the unlabelled first input data
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The limitation of store the unlabelled first input data is well-understood, routine, and conventional, as evidenced by MPEP §2106.05(d)(II)(iv), “Storing and retrieving information in memory”. This limitation therefore remains insignificant extra-solution activity even upon reconsideration, and does not amount to significantly more. Even when considered in combination, this additional element represents an insignificant extra-solution activity which cannot provide an inventive concept. The claim is not patent eligible.
Regarding claim 39, the rejection of claim 38 is further incorporated, and further, the claim recites: receive user-labelling of at least a portion of the stored unlabelled first data as belonging to a particular class of the second machine learning model; This limitation is mere data gathering thus is an insignificant extra-solution activity.
and adapt the second machine learning model by means of applying the user-labelled data to it as new training data. This limitation amounts to mere instructions to apply the judicial exception using a generic computer component. Please see MPEP 2106.05(f).
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The limitation of receive user-labelling of at least a portion of the stored unlabelled first data as belonging to a particular class of the second machine learning model is well-understood, routine, and conventional, as evidenced by MPEP §2106.05(d)(II)(I), “receiving or transmitting data over a network”. This limitation therefore remains insignificant extra-solution activity even upon reconsideration, and does not amount to significantly more. Even when considered in combination, this additional element represents an insignificant extra-solution activity which cannot provide an inventive concept. The claim is not patent eligible.
Regarding claim 40, the rejection of claim 39 is further incorporated, and further, the claim recites: wherein the instructions which, when executed by the at least one processor, further causes the apparatus to prompt said user-labelling via a user-interface of the apparatus. This limitation amounts to mere instructions to apply the judicial exception using a generic computer component. Please see MPEP 2106.05(f).
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 41, the rejection of claim 39 is further incorporated, and further, the claim recites: wherein the instructions which, when executed by the at least one processor, further causes the apparatus to identify, from the stored unlabelled first data, a portion of said data having the highest likelihood of belonging to a particular class. This claim recites additional mental steps in addition to the judicial exception identified in the rejection of claim 33, thus recites a judicial exception.
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 42, the rejection of claim 38 is further incorporated, and further, the claim recites: wherein the adapting of the first machine learning model further causes the apparatus to receive one or more unlabelled data values from the stored unlabelled first data; This is mere data gathering and is considered to be an insignificant extra-solution activity.
identify one or more semantically-similar data points to the one or more unlabelled data values, wherein the one or more semantically-similar data points comprise data semantically related to the unlabelled data; This claim recites additional mental steps in addition to the judicial exception identified in the rejection of claim 33, thus recites a judicial exception.
apply the second machine learning model to (i) the one or more unlabelled data values to generate an unlabelled model output, and (ii) the identified one or more semantically-similar data points to generate a semantically-similar model output; This limitation amounts to mere instructions to apply the judicial exception using a generic computer component. Please see MPEP 2106.05(f).
train the second machine learning model based on a loss function comprising an unsupervised training loss, wherein the unsupervised training loss is arranged to minimise an averaged divergence between: (i) the unlabelled model output, and (ii) the semantically-similar model output. This claim recites additional mathematical concepts in addition to the judicial exception identified in the rejection of claim 33, thus recites a judicial exception.
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The limitation of wherein the adapting of the first machine learning model further causes the apparatus to receive one or more unlabelled data values from the stored unlabelled first data is well-understood, routine, and conventional, as evidenced by MPEP §2106.05(d)(II)(iv), “Storing and retrieving information in memory”. This limitation therefore remains insignificant extra-solution activity even upon reconsideration, and does not amount to significantly more. Even when considered in combination, this additional element represents an insignificant extra-solution activity which cannot provide an inventive concept. The claim is not patent eligible.
Regarding claim 43, the rejection of claim 39 is further incorporated, and further, the claim recites: wherein the first and second input data is generated by one or more sensors provided on said apparatus and/or on one or more user devices associated or paired with said apparatus as part of a personal network of an individual user. This limitation amounts to mere instructions to apply the judicial exception using a generic computer component. Please see MPEP 2106.05(f).
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 44, the rejection of claim 43 is further incorporated, and further, the claim recites: wherein one or more of said apparatus and/or the one or more user devices include wearable device(s). This limitation amounts to mere instructions to apply the judicial exception using a generic computer component. Please see MPEP 2106.05(f).
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 45, the rejection of claim 43 is further incorporated, and further, the claim recites: wherein none of the first and second input data is received externally from the apparatus and/or from the one or more user devices associated or paired with said apparatus as part of the personal network. This limitation amounts to mere instructions to apply the judicial exception using a generic computer component. Please see MPEP 2106.05(f).
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 46, the rejection of claim 33 is further incorporated, and further, the claim recites: wherein the first and second machine learning models are trained to classify input data representing user motion to one of a plurality of the different classes representing respective activities. This limitation merely confines the use of the judicial exception to a field of use or technological environment. Please see MPEP 2106.05(h).
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 47, the rejection of claim 33 is further incorporated, and further, the claim recites: wherein the first and second machine learning models are trained to classify input data representing audio to one of a plurality of the different classes representing users or commands. This limitation merely confines the use of the judicial exception to a field of use or technological environment. Please see MPEP 2106.05(h).
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 48, it is substantially similar to claim 33 respectively, and is rejected for at least the same reasons therein.
Regarding claims 50-51, they are substantially similar to claims 38, and 43 respectively, and is rejected for at least the same reasons therein.
Regarding claim 52, it is substantially similar to claim 33 respectively, and is rejected for at least the same reasons therein. Claim 52 additionally requires analysis for A non-transitory computer-readable medium comprising program instructions stored thereon for performing however this is an additional element that amounts to mere instructions to apply the judicial exception using a generic computer component. Please see MPEP 2106.05(f).
Response to Arguments
Applicant's arguments filed 02/12/2026 have been fully considered but they are not persuasive.
Regarding the 35 U.S.C. §101 Rejection:
Applicant appears to assert that the claims and specification set forth the improvement to the technology utilized to training a second machine learning model by adapting a first machine learning model to provide a second machine learning by adding one or more new classes to a first number of classes. Examiner respectfully disagrees. Although, the specification does describe that the claimed invention may have advantages in reducing overall training time, reducing the amount of storage required to store the training data and also enabling efficient training in a large number of devices, the claim itself fails to reflect the disclosed improvement. The claim broadly and generically recites “training the second machine learning model using the first/second input data” without any details of the actual steps of the training process which would reflect the improvement disclosed in the specification. Applicant further refers to Ex parte Desjardins as it provides a similar position to show a technological improvement and integrate the claim into a practical application. However, the examiner asserts that the claims of the present invention do not reflect the technological improvement disclosed in the specification whereas Ex parte Desjardins’ claims were directed to an improved way of training a machine learning model thus were directed to improvements in the machine learning technology itself as disclosed in the specification of Desjardins. Therefore, examiner asserts the claims are not patent eligible and applicant’s arguments are not persuasive.
Regarding the Prior art rejection:
As noted in the last office action, the claims have been searched however no prior art, either alone or in combination, fairly discloses recitations of previous claims 34 and 49. Since these recitations have been incorporated into independent Claims 33, 48, and 52, the claims would be allowable if all other outstanding rejections were withdrawn.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL H HOANG whose telephone number is (571)272-8491. The examiner can normally be reached Mon-Fri 8:30AM-4:30PM.
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/MICHAEL H HOANG/PRIMARY EXAMINER, Art Unit 2122